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This paper describes an Intelligent Tutoring System that provides adaptable facilities to students over the World Wide Web. The system is able to adapt to a large corpus of students, in terms of allowing commonly used paths to emerge, and adapts to individual students by employing a novel student model.
The lack of intelligent tutoring systems outside of academic research has largely been attributed to the fact that they are domain specific. Whilst very powerful for the tutoring of a specific subject, the inability of a knowledge-based approach to artificial intelligence to generalise that has rendered it less useful for generic systems. Neural networks, or connectionist models, are the antithesis of knowledge-based approaches in that they are extremely adept at generalising which gives them the ability to work with very noisy data.
The research project described in the paper employs both knowledge-based representations and neural networks to model students using non-domain......

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Approximate Word Count: 3050
Approximate Pages: 13 (250 words per double-spaced page)

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